{"id":"https://openalex.org/W18433384","doi":null,"title":"Clustering Facial Displays in Context","display_name":"Clustering Facial Displays in Context","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W18433384","mag":"18433384"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.118.9781","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.9781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.toronto.edu/~jhoey/papers/TR-01-17.ps.gz","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3732,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67665512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.4377000033855438,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.4377000033855438,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.33980000019073486,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.07360000163316727,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/facial-movement","display_name":"facial motion","score":0.7509999871253967},{"id":"https://openalex.org/keywords/embodied-agents","display_name":"embodied agents","score":0.753000020980835},{"id":"https://openalex.org/keywords/optical-flow","display_name":"optical flow","score":0.6240000128746033},{"id":"https://openalex.org/keywords/zernike-polynomials","display_name":"Zernike polynomials","score":0.9890000224113464},{"id":"https://openalex.org/keywords/hidden-markov-models","display_name":"hidden Markov models","score":0.925000011920929},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"facial expression recognition","score":0.5580000281333923},{"id":"https://openalex.org/keywords/face-tracking","display_name":"face tracking","score":0.7440000176429749},{"id":"https://openalex.org/keywords/video-segmentation","display_name":"video segmentation","score":0.4269999861717224}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7062608599662781},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6890036463737488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676681637763977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5617666244506836},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5597385168075562},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5537119507789612},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.530147910118103},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48515114188194275},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4851325452327728},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.4175163805484772},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4141477942466736},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1327354907989502},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09046110510826111},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.118.9781","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.9781","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.toronto.edu/~jhoey/papers/TR-01-17.ps.gz","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W147920510","https://openalex.org/W1509031088","https://openalex.org/W1548872565","https://openalex.org/W1565443366","https://openalex.org/W1636244751","https://openalex.org/W1748696506","https://openalex.org/W1850070871","https://openalex.org/W1988223947","https://openalex.org/W2022672617","https://openalex.org/W2049633694","https://openalex.org/W2100315781","https://openalex.org/W2106390385","https://openalex.org/W2108308566","https://openalex.org/W2109269337","https://openalex.org/W2131709365","https://openalex.org/W2132875213","https://openalex.org/W2133658970","https://openalex.org/W2137883513","https://openalex.org/W2138043589","https://openalex.org/W2138451337","https://openalex.org/W2141933285","https://openalex.org/W2152553986","https://openalex.org/W2158199973","https://openalex.org/W2158815872","https://openalex.org/W2173491568","https://openalex.org/W2254592486"],"related_works":["https://openalex.org/W2167287689","https://openalex.org/W7098408097","https://openalex.org/W2109328551","https://openalex.org/W2542517113","https://openalex.org/W1969014310","https://openalex.org/W1503930725","https://openalex.org/W2554620633","https://openalex.org/W1973845020","https://openalex.org/W1557274483","https://openalex.org/W2058479252"],"abstract_inverted_index":{"Abstract":[0],"A":[1,64],"computer":[2],"user's":[3],"facial":[4,81],"displays":[5],"will":[6,20],"be":[7],"context":[8],"dependent,":[9],"especially":[10],"in":[11,24,41,93],"the":[12,42,53,57,73,86,105],"presence":[13],"of":[14,39,61,67,77,90,107,113],"an":[15],"embodied":[16],"agent.":[17],"Furthermore,each":[18],"interactant":[19],"use":[21],"their":[22],"face":[23,97],"different":[25,28],"ways,":[26],"for":[27,36,110],"purposes.":[29],"These":[30],"two":[31],"hypotheses":[32],"motivate":[33],"a":[34,95,111],"method":[35],"clustering":[37,87],"patterns":[38,108],"motion":[40,46],"human":[43],"face.":[44],"Facial":[45],"is":[47,98],"described":[48],"using":[49],"optical":[50],"flow":[51],"over":[52],"entire":[54],"face,":[55],"projectedto":[56],"complete":[58],"orthogonal":[59],"basis":[60],"Zernike":[62],"polynomials.":[63],"context-dependent":[65],"mixture":[66],"hidden":[68],"Markov":[69],"models":[70],"(cmHMM)":[71],"clusters":[72],"resulting":[74],"temporal":[75],"sequences":[76],"feature":[78],"vectors":[79],"into":[80],"display":[82],"classes.":[83],"We":[84,103],"apply":[85],"technique":[88],"tosequences":[89],"continuous":[91],"video,":[92],"which":[94],"single":[96],"tracked":[99],"and":[100],"spatially":[101],"segmented.":[102],"discuss":[104],"classes":[106],"uncovered":[109],"number":[112],"subjects.":[114]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-27T00:00:00"}
